USAGE OF ARITIFICIAL INTELLIGENCE IN AIDING WITH COLONIC SESSILE SERRATED LESIONS DETECTION AND DIAGNOSIS (AI-SSLD)
Status: Recruiting
Location: See all (3) locations...
Intervention Type: Device
Study Type: Interventional
Study Phase: Not Applicable
SUMMARY
The aim of this study is to is to evaluate if a real-time Computer Aided Detection (CADe) system can help improve the detection of SSL(sessile serrated lesions) versus a conventional colonoscopy (CC) using white light examination(WLE).
Eligibility
Participation Requirements
Sex: All
Minimum Age: 40
Maximum Age: 80
Healthy Volunteers: t
View:
• Adult (40 - 80 years) Undergoing colonoscopy for screening, surveillance, or diagnostic indications. Complete colonoscopy with satisfactory Boston Bowel Prep Scale of 6 or higher. Provide informed consent to participate in the study
Locations
Other Locations
Singapore
Changi General Hospital
NOT_YET_RECRUITING
Singapore
National University of Singapore
RECRUITING
Singapore
Tan Tock Seng Hospital
RECRUITING
Singapore
Contact Information
Primary
Weida Chew, Masters
wei.da.chew@nhghealth.com.sg
63577897
Backup
Aei Aei Zaw
aei.aei.zaw@nhghealth.com.sg
63573116
Time Frame
Start Date: 2026-05-21
Estimated Completion Date: 2027-05-03
Participants
Target number of participants: 628
Treatments
Active_comparator: AI-assisted colonoscopy
No_intervention: Conventional Colonoscopy
Conventional Colonoscopy using white light
Related Therapeutic Areas
Sponsors
Collaborators: National University Health System, Singapore, Changi General Hospital
Leads: National Healthcare Group, Singapore